In this paper we study income polarization by first comparing the efficiency of two statistical models to identify the number of poles in the income distribution empirically. The statistical models used are a multi-resolution analysis (MRA) and a log-normal approach (LNA). We then apply the methodology to Israeli income data over the years 1997−2008 in order to empirically detect the number of income classes as sub-populations of incomes concentrated around an optimally determined number of poles. After that we compute polarization using a multiplicative normalized polarization measure, developed by Palacios-González and García-Fernández (An Intra-Group Variance Based Polarization Measure, 2010), which consists of three interacting components based on well-known axioms of Esteban and Ray (Extensions of a Measure of Polarization OCDE Countries, 1994). Finally we study the causes of the obtained polarization results in a multinomial logit analysis.